Slice encoding for constraint-based planning

Authors:
Cédric Pralet;Gérard Verfaillie
Affiliations:
ONERA, Toulouse Cedex 4, France;ONERA, Toulouse Cedex 4, France
Venue:
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
Year:
2009

Citing 8
Cited 0

Planning as satisfiability

ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
CPlan: a constraint programming approach to planning

AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Planning as constraint satisfaction: solving the planning graph by compiling it into CSP

Artificial Intelligence
Constraint-Based Attribute and Interval Planning

Constraints
Automated Planning: Theory & Practice

Automated Planning: Theory & Practice
Handbook of Constraint Programming (Foundations of Artificial Intelligence)

Handbook of Constraint Programming (Foundations of Artificial Intelligence)
PDDL2.1: an extension to PDDL for expressing temporal planning domains

Journal of Artificial Intelligence Research
Generalizing GraphPlan by formulating planning as a CSP

IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

In most of the constraint-based approaches to planning, the problem is unfolded over a given number of steps. Because this unfolded CSP encoding is very time and memory consuming, we propose on top of the CNT framework (Constraint Networks on Timelines) a more efficient slice CSP encoding which allows only a limited number of steps to be considered at each step of the search.